“Isn’t it obvious?” (the PACSMan) asked. “Here’s the deal. No one knows where healthcare is going, so we’re all going to start enjoying Thanksgiving again for the first time in 75 years. Instead of freezing our asses off, we’ll do an interactive virtual conference with scheduled demos and everything. No muss, no fuss, and no ‘free’ meals. As a bonus, system prices will drop 30% because vendors won’t have to pay for RSNA. It’s sheer brilliance, I tell ya!"Mike was referring to the vendor extravaganza at RSNA, but I think this applies to site-visits as well. There is simply no need to haul people across the countryside (or country, for that matter) to see the scanner. They all look pretty much the same, and decisions are not made on the basis of their appearance. (Bore size and other specs are important, but that's all in the specs.)
Dalai's note: This piece is reprinted from today's American Thinker. It is one of the most eloquent, heartfelt, and most importantly, ACCURATE renditions of the Mideast situation today. It is a long essay, but well worth your time. Know the history. Know the TRUTH.
In a Receiver Operating Characteristic (ROC) curve the true positive rate (Sensitivity) is plotted in function of the false positive rate (100-Specificity) for different cut-off points. Each point on the ROC curve represents a sensitivity/specificity pair corresponding to a particular decision threshold. A test with perfect discrimination (no overlap in the two distributions) has a ROC curve that passes through the upper left corner (100% sensitivity, 100% specificity). Therefore the closer the ROC curve is to the upper left corner, the higher the overall accuracy of the test (Zweig & Campbell, 1993).Got it? Just remember that everybody's ROC is going to be different, with different blends of sensitivity and specificity.
So what is quality? I guess getting it right every time would be a good start. But that really isn't in the realm of human performance. No one has a vertical ROC curve. If you read enough X-rays and scans, you will miss something. The old saying goes that the only way not to miss anything is not to read anything. That's not very practical.
Who Is the Better Radiologist?By SAURABH JHA, MD
There’s a lot of talk about quality metrics, pay for performance, value-based care and penalties for poor outcomes.
In this regard, it’s useful to ask a basic question. What is quality? Or an even simpler question, who is the better physician?
Let’s consider two fictional radiologists: Dr. Singh and Dr. Jha.
Dr. Singh is a fast reader. Her turn-around time for reports averages 15 minutes. Her reports are brief with a paucity of differential diagnoses. The language in her reports is decisive and her reports contain very few disclaimers. She has a high specificity meaning that when she flags pathology it is very likely to be present.
The problem is her sensitivity. She is known to miss subtle features of pathology.
There’s another problem. Sometimes when reading her reports one isn’t reassured that she has looked at every organ. For example, her report of a CAT scan of the abdomen once stated that “there is no appendicitis. Normal CT.” The referring physician called her wondering if she had looked at the pancreas, since he was really worried about pancreatitis not appendicitis. Dr. Singh had, but had not bothered to enlist all normal organs in the report.
Dr. Jha is not as fast a reader as Dr. Singh. His turn-around time for reports averages 45 minutes. His reports are long and verbose. He meticulously lists all organs. For example, when reporting a CAT of the abdomen of a male, he routinely mentions that “there is no gross abnormalities in the seminal vesicles and prostate,” regardless of whether pathology is suspected or absence of pathology in those organs is of clinical relevance.
He presents long list of possibilities, explaining why he thinks a diagnosis is or is not. He rarely comes down on a specific diagnosis.
Dr. Jha almost never misses pathology. He picks up tiny lung cancers, subtle thyroid cancers and tiny bleeds in the brain. He has a very high sensitivity. This means that when he calls a study normal, and he very rarely does, you can be certain that the study is normal.
The problem with Dr. Jha is specificity. He often raises false alarms such as “questionable pneumonia,” “possible early appendicitis” and “subtle high density in the brain, small punctate hemorrhage not entirely excluded.”
In fact, his colleagues have jokingly named a scan that he recommends as “The Jha Scan Redemption.” These almost always turn out to be normal.
Which radiologist is of higher quality, Dr. Singh or Dr. Jha?
If you were a patient who would you prefer read your scan, the under calling, decisive Dr. Singh or the over calling, painfully cautious Dr. Jha?
If you were a referring physician which report would you value more, the brief report with decisive language and a paucity of differential diagnoses or the lengthy verbose report with long lists on the differential?
If you were the payer which radiologist would you wish the hospital employed, the one who recommended fewer studies or the one who recommended more studies?
If you were a hospital administrator which radiologist would you award a higher bonus, the fast reading Singh or the slow reading Jha? This is not a slam dunk answer because the slow-reading over caller generates more billable studies.
If you were hospital’s Quality and Safety officer or from Risk Management, who would you lose more sleep over, Dr. Singh’s occasional false negatives or Dr. Jha’s frequent false positives? Note, it takes far fewer false negatives to trigger a lawsuit than false positives.
I suppose you would like hard numbers to make an “informed” decision. Let me throw this one to you.
For every 10, 000 chest x-rays Dr. Singh reads, she misses one lung cancer. Dr. Jha does not miss a single lung cancer, but he recommends 200 CAT scans of the chest for “questionable nodule” per 10, 000 chest x-rays. That is 200 more than Dr. Singh. And 199/ 200 of these scans are normal.
I can hear the siren song of an objection. Why can’t a physician have the sensitivity of Dr. Jha and the specificity of Dr. Singh? The caution of Jha and the speed of Singh? The decisiveness of Singh and the comprehensiveness of Jha?
You think I’m committing a bifurcation fallacy by enforcing a false dichotomy. Can’t we have our specificity and eat it?
Sadly, I’m not. It is a known fact of signal theory that no matter how good one is, there is a trade-off between sensitivity and specificity. Meaning if you want fewer false negatives, e.g. fewer missed cancers on chest X-ray, there will be more false positives, i.e. negative CAT scans for questioned findings on chest X-ray.
Trade-off is a fact of life. Yes, I know it’s very un-American to acknowledge trade-offs. And I respect the sentiment. The country did, after all, send many men to the moon.
Nevertheless, whether we like it or not trade-offs exist. And no more so than in the components that make up the amorphous terms “quality” and “value.”
Missing cancer on a chest x-ray is poor quality (missed diagnosis). Over calling a cancer on a chest x-ray which turns out to be nothing is poor quality (waste). But now you must decide which is poorer. Missed diagnosis or waste? And by how much is one poorer than the other.
That’s a trade-off. Because if you want to approach zero misses there will be more waste. And if we don’t put our cards on the table, “quality” and “value” will just be meaningless magic talk. There, I just gave Hollywood an idea for the next Shrek, in which he breaks the iron triangle of quality, access and costs and rescues US healthcare.
If I had a missed cancer on a chest x-ray I would have wanted Dr. Jha to have read my chest x-ray. If I had no cancer then I would have wanted Dr. Singh to have read my chest x-ray. Notice the conditional tense. Conditional on knowing the outcome.
In hindsight, we all know what we want. Hindsight is just useless mental posturing. The tough proposition is putting your money where your mouth is before the event. Before you know what will happen.
This is the ex-ante ex-post dilemma. In case you want a clever term for what is patently common sense.
Dr. Singh is admired until she misses a subtle cancer on a chest x-ray. Then Risk Management is all over her case wondering why? How? What systems must we change? What guidelines must we incorporate?
Really? Must you ask?
Dr. Jha, on the other hand, is insidiously despised and ridiculed by everyone. All who remain unaware that he is merely a product of the zero risk culture in the bosom of which all secretly wish to hide.
The trouble with quality is not just that it is nebulous in definition and protean in scope. It can mean whatever you want it to mean on a Friday. It is that it comprises elements that are inherently contradictory.
Society, whatever that means these days, must decide what it values, what it values more and how much of what it values less is it willing to forfeit to attain what it values more.
Before you start paying physicians for performance and docking them for quality can we be precise about what these terms mean, please?
- Radiologists error rate reported at 30%
- >70% perceptual
- abnormality is not perceived, i.e. “missed”
- <30% cognitive
- Abnormality is perceived but misinterpreted
- Error does not equal negligence
- Negligence occurs when the degree of error exceeds an accepted standard
- Missed diagnoses are the major reason radiologists are sued
- Most commonly missed:
- Cancers (breast and lung are the largest percentacge)
- Spine fractures
- Retrospective error/miss rate averages 30% (i.e. hindsight is 20-20)
- “Real-time” error rate in daily practice averages 3-5%
I've got enough friends who happen to be litigators to know that two things drive a malpractice suit: anger and greed/envy, and they go hand-in-hand. (And as an aside, the majority of cases appear to reach the attention of a lawyer because ANOTHER DOCTOR told the patient that something wasn't done as well as HE would have done it.) As with the young lady driving the beat-up car, an accident or even an incident that approaches such is enough to promote rage in some of us, perhaps even most of us. It doesn't matter that the act was unintentional. I did not set out yesterday to trash some kid's little red jalopy. I think it's also reasonable to say that no physician decides some morning to cause harm to his patient. A missed finding, like a parking-lot collision, is an accident. It is not meant to happen, and everyone would prefer that it doesn't. This is where greed and envy can augment the madness of rage. The young lady above, at some level, realized that my truck was likely worth 8-10 times what her beater might bring, and no doubt this got her all the more riled. Why should that doofus have a nice car? Who gave him the right to almost plow into me? He must think he owns the road, having an expensive car like that. I'll show him!Hopefully the above discussion of sensitivity and specificity brings this all full-circle. You can see the pressures under which we operate. We are to produce the work with decisive reports one after the other after the other, functioning as Dr. Singh, but we are never to miss anything, wearing the Dr. Jha hat. Why not just do both? Because we are human and humans can't do that.
In the case of a miss or other adventure in medical errors, I think the same thing applies, although certainly with a little more justification. There is clearly a relationship between doctor and patient. If something goes wrong, the patient feels betrayed And the patient gets angry. Given the perception of docs as wealthy, the next step in the mental equation may become: he hurt me (or could have hurt me) and he's going to pay! He can afford it!
While a financial award could put a car back together again, it may not be able to fix what was broken by the medical error. Somewhere along the way, our society has decided that money can compensate for the damage, and maybe that is true. However, juries of our "peers" are wont to award huge sums as punitive measure to "punish" the "bad" doctor. And let us not forget the fact that the litigator might receive 30-50% of the proceeds.
This is wrong. The whole scenario is horrible, and accomplishes nothing but padding the pockets of the litigating AND the defending lawyers. It leads to millions and billions of dollars spent for "cover your ass" procedures and tests. And it's all predicated on the anger over an accident and the thought that there might be a gold-mine to be had having won the malpractice lottery. This must stop.
I want this to be Mar-Mar's legacy: we must forgive those who make honest mistakes. We need to remove anger, greed and envy (and lawyers) from the equation, and somehow set up some entity, some body or board, that would determine actual damages and arrange for those to be made as whole as possible, but without multi-million dollar punitive, redistributive, awards. I know this is next to impossible, as there is way too much money to be made by trying "rich" doctors in front of a jury of their "peers" who would love nothing more than to sock it to them. But it is the right thing, and all but those who profit from the malpractice industry, not just the lawyers, but the plaintiff whores who sell their testimony, know that I'm spot on. Mar-Mar would approve.
September arrives next Monday, signifying for most the end of summer, which means families with children are starting to settle back into a steady schedule and routine that allows for more consistent time to focus on work, on learning, and on reaching the end of 2014 on a positive note.
Here at HL7standards.com we have always operated under the principal of “Engaging conversations on healthcare and technology.” We work to accomplish this through our blog posts that span the wide swath of healthcare technology and through social media interaction that is more conversational and collaborative as opposed to a preacher with a bullhorn.
Our collaborative approach is best illustrated through our weekly #HITsm Tweetchats, which involve thoughtful discussions on topics that seemingly cover each “silo” of healthcare technology. If we’re not learning from each other through technology then we’re not social, we’re not curious, and we’re probably not very interesting, in my opinion.
It is with this collaborative and learning spirit that I am pleased to announce a new project I’ve dubbed “20 Questions for Health IT.”
We hope this project, which covers the entire month of September, will take the interaction of our social media discussions one step deeper and allow more time to discuss 20 different topics currently influencing the health IT industry.
Beginning Tuesday, Sept. 2., we will begin publishing one health IT topic per day from 20 different individuals with a deep understanding of the topic. The author of each question was generous enough to stick her or his neck out and pose a short answer to the question in the hopes it will encourage further discussion in the comments section and also on Twitter using the #20HIT tag.
So stay tuned next week as we launch into a month-long discussion that hopefully will educate and just maybe lead to a breakthrough idea that will evolve into something bigger.
Special thanks to each contributor
Sept. 2. Chad Johnson
Sept. 3. Don Fluckinger
Sept. 4. Michelle Ronan Noteboom
Sept. 5. Bernadette Keefe, MD
Sept. 8. Leonard Kish
Sept. 9. Greg Meyer
Sept. 10. Nick van Terheyden, MD
Sept. 11. Hubert Zajicek, MD
Sept. 12. Angela Dunn
Sept. 15. Rob Brull
Sept. 16. Mandi Bishop
Sept. 17. David Muntz
Sept. 18. Grahame Grieve & Rasu Shrestha, MD (Two for National Health IT Week)
Sept. 19. Scott Mace
Sept. 22. Jon Mertz
Sept. 23. Jenn Dennard
Sept. 24. Steven Posnack
Sept. 25. Vince Kuraitis
Sept. 26. Brian Eastwood
Dates subject to change
A few weeks ago, I wrote about engaged patients and how they had lower healthcare costs and better health outcomes. While there is no one official definition of patient engagement, I see engaged patients as those who are interested in their health outcomes and who actively participate in their care by working with their healthcare providers to create goals.
Most healthcare professionals can attest that not all patients are necessarily engaged in their care. Some patients are very interested in achieving goals and outcomes and others don’t seem at all interested in participating in their care. How do we get those in the second group to become more participatory and invested in their care? Interactive patient care might be one way to get them on board.
Interactive patient care is a means of providing education to patients through technology like mobile devices and televisions. Interactive patient care allows patients to be active participants in their care rather than just passive recipients of information and instructions.
A June 2014 article in Healthcare Finance News, gives an example of interactive patient care at work. Boston’s South Shore Hospital and Brigham and Women’s Hospital created a pilot project that used a mobile application to connect with cardiac rehabilitation patients. The app allowed patients to check daily to-do lists, to log exercise, to remind themselves to take medications, and to interact directly with clinicians. The project appears to have improved patient engagement and interaction. In the article, South Shore nurse manager Karen LaFond explained that while cardiac rehabilitation programs have been shown to decrease mortality rates, many patients don’t take part in them. However, patient retention and compliance with cardiac rehabilitation care plans have significantly improved when using mobile applications.
Another example of interactive patient care is GetWell Network’s pediatric tool GetWell Town.It was developed to help patients and families learn and play during their hospital stay. GetWell Town can be accessed at the patient’s bedside through an iPad or television and offers age-appropriate entertainment, education and other content. The system covers information on topics like asthma, diabetes and various procedures. The GetWell website describes the presentation of information as “colorful and interactive.” It certainly grabbed the attention of my 3-year-old who saw the website over my shoulder as I was typing this and asked, “Can we play that?”
Play, while not always technology based, is the ultimate form of interactivity and one physician is combining technology with old school play to combat childhood obesity. Dr. Robert Zarr’s, a Washington, D.C.-based pediatrician, approach to managing obesity was featured on NPR in July. To get children to increase their activity, he writes prescriptions for daily play and activity. To make the prescriptions more specific, he has mapped out all of the district’s 380 parks and developed a searchable database that can be linked to patients’ medical records.
Think about ways we can make health promotion fun. Wouldn’t having a cooking contest along the lines of Chopped (where you are provided mystery ingredients and have to create a great tasting dish) for diabetic patients be more interesting than just handing them a piece of paper that tells them to keep their carbs under a certain number per day? It might inspire them to get creative and have fun in their own kitchens coming up with recipes that meet dietary requirements. And that would help them better adhere to their diets.
Interactivity, and not just technological interactivity, may be the secret to getting patients engaged. Doing is infinitely more interesting than being talked at or just handed information. That’s why we do science experiments in school. Theory is one thing but seeing an idea in action, and being a part of that action, makes the concepts so much more concrete. Making the action fun just adds to the chances of success. That’s why nursery rhymes and the ABC song have been used as learning tools for decades.
My generation was raised on video games, even if it was Galaga and Ms. Pac-Man. My daughter’s generation is being raised on smart phone apps and tablet computers. We like technology that can provide us with fun and feedback. And no matter what age you are – from 80 to 8 – when learning is fun, no matter what form it takes, the information tends to stick and this leads to better health outcomes.
It is apparent as we move toward value-based care and payments, that health care is dependent on so much more than what we would consider care. It’s not all up to the provider nor up to the individual patient, there’s a wide network of costs and influences from genetics to nutrition.
As we move toward digital health and digital payments, the relationships between spending, environment, and other health determinants are becoming clearer, affecting the choices we make at any moment. Behavioral choices are often driven by the social determinants of health, the cultural and economic contexts (including geography) of our day-to-day decisions.
Many things, of course, influence health and outcomes and our need for care, including, genetics, behavioral choices (smoking, drugs, alcohol, unprotected sex, obesity, preventative care, exercise, taking prescribed medications, sugar intake and nutrition), access to care, capabilities to care for oneself and many other risks.
While we tend to think in terms of science and individuals controlling outcomes, that’s at the very least a bit of hubris on the part of science. Zip codes were recently declared better at predicting outcomes than genetic codes (hat tip to Cyndy Nayer).
And these social influences are becoming better understood, because we are getting better at measuring them, with access to better data, as a byproduct of ubiquitous connectivity (although extent of connectivity is often correlated with zip code as well). We often assume that it’s all up to the individual, but most of what we do is a combination of many things including marketing, education, costs, and culture. As we spend more time online, those influences become both greater and more measurable. Tremendous value will be seen once we understand these decisions and why people make them, including social, economic and geographic influences in the context of vast networks of influences.
The impact numbers of personal choice and behavior related to health and health care spending, when you dig in, are pretty staggering, and perhaps, devastating for our financial outlook.
“Consumption of junk food (for example a Twinkie or a sugary drink) is akin to a financial exchange where short-term gains are privatized and long-term costs are socialized in the form of horrific health outcomes. The metabolic donkeys – consumers – pay relatively little money and turn a blind eye to the health consequences of their food choices – instead hoisting the fantastic profits of companies like Monster and opting for a shortened, diseased life.”
In the Forbes article, Munro estimates that sugar may be costing the U.S. healthcare system $1 trillion. That’s 25% of healthcare’s overall $4 trillion. Estimates are that Americans eat 70 lbs of sugar a year. Even at a rather high price of $1 a pound (commodity prices are around 15 cents per pound), that’s only about $25 billion that we spend on sugar as a country for the ingredient itself (certainly we pay much more for it when it comes in a soda or Monster beverage, or myriad of other products). So the costs of sugar to the healthcare system are on the order of 40 times higher than the price of sugar itself. Sugar, or a cigarette, is very small down payment on future health costs.
Prices and financial incentives are too often left out of the equation because we haven’t found the right mix. Offering salads at McDonald’s might not work, we don’t go to McDonald’s for salads, wrong context. Low-income women, on the other hand, might be incentivized to buy and eat vegetables, and at least in limited contexts, we do see that vouchers like this can work.
Carolyn Dimitri, an applied economist at New York University, tested whether farmer’s markets vouchers would not only encourage low-income women to buy and eat more vegetables using vouchers and measuring with surveys. They found that vouchers not only encouraged the purchasing, but also the consumption of more vegetables.
According to Pacific Standard’s write-up of the article, “..this suggests that disadvantaged families may eat fewer vegetables not because of preferences or education but because of access…(and possibly) economic scarcity and its psychological effects.”
To truly understand the health system, not just the healthcare system, we’ll need to understand decisions and incentives around food. Patient engagement has direct effects on health outcomes and health spending, as has been shown many times. How closely tied is nutrition to outcomes? Certainly it’s more long-term, but we need to understand correlations and causations much sooner.
Could providers or payers benefit by providing nutritional vouchers? Is there an app or technological solution that works for reducing sugar intake?
This is one area of mobile health and app development we hear little about, despite the fact that diabetes, prediabetes, and metabolic syndrome affect more than 40% of Americans, or over 100 million people. These are Americans that will have long-term health consequences and costs.
Why aren’t we doing more to help? Is it just too hard? Is our sugar addiction just too strong? What will Apple do now that they are including Healthkit in IOS8? What can Stikk do to improve on sugar intake?
This may be one of the most difficult, but also one of the most valuable, quests in healthcare.
Who else stands to benefit from reducing the $1 trillion in sugar-related health spending? How quickly can nutritions steer some of that money, much larger than that spent on sugar, toward better health and better nutritional decisions?
Moving just a little bit of the money we spend on sugar and on sugar-related diseases will pay enormous dividends in quality of life and cost of care. At VivaPhi, we’re rolling with the Center of Health Engagement, driving new incentive programs to drive better engagement and better health. Have an idea for how to create these kinds of incentives for healthier choices? We want to hear them.
Healthcare executives are continuously evaluating the subject of RFID and RTLS in general. Whether it is to maintain the hospitals competitive advantage, accomplish a differentiation in the market, improve compliance with requirements of (AORN, JCAHO, CDC) or improve asset utilization and operating efficiency. As part of the evaluations there is that constant concern around a tangible and measurable ROI for these solutions that can come at a significant price.
When considering the areas that RTLS can affect within the hospital facilities as well as other patient care units, there are at least four significant points to highlight:
Disease surveillance: With hospitals dealing with different challenges around disease management and how to handle it. RTLS technology can determine each and every staff member who could have potentially been in contact with a patient classified as highly contagious or with a specific condition.
Hand hygiene compliance: Many health systems are reporting hand hygiene compliance as part of safety and quality initiatives. Some use “look-out” staff to walk the halls and record all hand hygiene actives. However, with the introduction of RTLS hand hygiene protocol and compliance when clinical staff enter or use the dispensers can now be dynamically tracked and reported on. Currently several of the systems that are available today are also providing active alters to the clinicians whenever they enter a patient’s room and haven’t complied with the hand hygiene guidelines.
Locating equipment for maintenance and cleaning:
Having the ability to identify the location of equipment that is due for routine maintenance or cleaning is critical to ensuring the safety of patients. RTLS is capable of providing alerts on equipment to staff.
A recent case of a hospital spent two months on a benchmarking analysis and found that it took on average 22 minutes to find an infusion pump. After the implementation of RTLS, it took an average of two minutes to find a pump. This cuts down on lag time in care and can help ensure that clinicians can have the tools and equipment they need, when the patient needs it.
There are also other technologies and products which have been introduced and integrated into some of the current RTLS systems available.
There are several RTLS systems that are integrated with Bed management systems as well as EHR products that are able to deliver patient order status, alerts within the application can also be given. This has enabled nurses to take advantage of being in one screen and seeing a summary of updated patient related information.
Unified Communication systems:
Nurse calling systems have enabled nurses to communicate anywhere the device is implemented within the hospital facility, and to do so efficiently. These functionalities are starting to infiltrate the RTLS market and for some of the Unified Communication firms, it means that their structures can now provide a backbone for system integrators to simply integrate their functionality within their products.
In many of the recent implementations of RTLS products, hospital executives opted to deploy the solutions within one specific area to pilot the solutions. Many of these smaller implementations succeed and allow the decision makers to evaluate and measure the impacts these solutions can have on their environment. There are several steps that need to be taken into consideration when implementing asset tracking systems:
• Define the overall goals and driving forces behind the initiative
• Develop challenges and opportunities the RTLS solution will be able to provide
• Identify the operational area that would yield to the highest impact with RTLS
• Identify infrastructure requirements and technology of choice (WiFi based, RFID based, UC integration, interface capability requirements)
• Define overall organizational risks associated with these solutions
• Identify compliance requirements around standards of use
RFID is one facet of sensory data that is being considered by many health executives. It is providing strong ROI for many of the adapters applying it to improve care and increase efficiency of equipment usage, as well as equipment maintenance and workflow improvement. While there are several different hardware options to choose from, and technologies ranging from Wi-Fi to IR/RF, this technology has been showing real value and savings that health care IT and supply chain executives alike can’t ignore.
It was not long after mankind invented the wheel, carts came around. Throughout history people have been mounting wheels on boxes, now we have everything from golf carts, shopping carts, hand carts and my personal favorite, hotdog carts. So you might ask yourself, “What is so smart about a medical cart?”
Today’s medical carts have evolved to be more than just a storage box with wheels. Rubbermaid Medical Solutions, one of the largest manufacturers of medical carts, have created a cart that is specially designed to house computers, telemedicine, medical supply goods and to also offer medication dispensing. Currently the computers on the medical carts are used to provide access to CPOE, eMAR, and EHR applications.
With the technology trend of mobility quickly on the rise in healthcare, organizations might question the future viability of medical carts. However a recent HIMSS study showed that cart use, at the point of care, was on the rise from 26 percent in 2008 to 45 percent in 2011. The need for medical carts will continue to grow; as a result, cart manufacturers are looking for innovative ways to separate themselves from their competition. Medical carts are evolving from healthcare products to healthcare solutions. Instead of selling medical carts with web cameras, carts manufacturers are developing complete telemedicine solutions that offer remote appointments throughout the country, allowing specialist to broaden their availability with patients in need. Carts are even interfaced with eMAR systems that are able to increase patient safety; the evolution of the cart is rapidly changing the daily functions of the medical field.
Some of the capabilities for medical carts of the future will be to automatically detect their location within a healthcare facility. For example if a cart is improperly stored in a hallway for an extended period of time staff could be notified to relocate it in order to comply to the Joint Commission’s requirements. Real-time location information for the carts could allow them to automatically process tedious tasks commonly performed by healthcare staff. When a cart is rolled into a patient room it could automatically open the patient’s electronic chart or give a patient visit summary through signals exchanged between then entering cart and the logging device kept in the room and effectively updated.
Autonomous robots are now starting to be used in larger hospitals such as the TUG developed by Aethon. These robots increase efficiency and optimize staff time by allowing staff to focus on more mission critical items. Medical carts in the near future will become smart robotic devices able to automatically relocate themselves to where they are needed. This could be used for scheduled telemedicine visits, the next patient in the rounding queue or for automated medication dispensing to patients.
Innovation will continue in medical carts as the need for mobile workspaces increase. What was once considered a computer in a stick could be the groundwork for care automation in the future.
This has been an eventful year for speech recognition companies. We are seeing an increased development of intelligence systems that can interact via voice. Siri was simply a re-introduction of digital assistants into the consumer market and since then, other mobile platforms have implemented similar capabilities.
In hospitals and physician’s practices the use of voice recognition products tend to be around the traditional speech-to-text dictation for SOAP (subjective, objective, assessment, plan) notes, and some basic voice commands to interact with EHR systems. While there are several new initiatives that will involve speech recognition, natural language understanding and decision support tools are becoming the focus of many technology firms. These changes will begin a new era for speech engine companies in the health care market.
While there is clearly tremendous value in using voice solutions to assist during the capture of medical information, there are several other uses that health care organizations can benefit from. Consider a recent product by Nuance called “NINA”, short for Nuance Interactive Natural Assistant. This product consists of speech recognition technologies that are combined with voice biometrics and natural language processing (NLP) that helps the system understand the intent of its users and deliver what is being asked of them.
This app can provide a new way to access health care services without the complexity that comes with cumbersome phone trees, and website mazes. From a patient’s perspective, the use of these virtual assistants means improved patient satisfaction, as well as quick and easy access to important information.
Two areas we can see immediate value in are:
Customer service: Simpler is always better, and with NINA powered Apps, or Siri like products, patients can easily find what they are looking for. Whether a patient is calling a payer to see if a procedure is covered under their plan, or contacting the hospital to inquire for information about the closest pediatric urgent care. These tools will provide a quick way to get access to the right information without having to navigate complex menus.
Accounting and PHR interaction: To truly see the potential of success for these solutions, we can consider some of the currently used cases that NUANCE has been exhibiting. In looking at it from a health care perspective, patients would have the ability to simply ask to schedule a visit without having to call. A patient also has the ability to call to refill their medication.
Nuance did address some of the security concerns by providing tools such as VocalPassword that will tackle authentication. This would help verify the identity of patients who are requesting services and giving commands. As more intelligence voice-driven systems mature, the areas to focus on will be operational costs, customer satisfaction, and data capture.
[...] medical practice billing software encourage [...]
Given the number of breaches we’ve seen this Summer at healthcare institutions, I’ve just spent a ton of time recently on several engineering engagements looking at “HIPAA compliant” encryption (HIPAA compliance is in quotes since it’s generally meaningless). Since I’ve heard a number of developers say “we’re HIPAA compliant because we encrypt our data” I wanted to take a moment to unbundle that statement and make sure we all understand what that means. Cryptology in general and encryption specifically are difficult to accomplish; CISOs, CIOs, HIPAA compliance officers shouldn’t just believe vendors who say “we encrypt our data” without asking for elaboration in these areas:
When you look at encrypting data, it’s not just “in transit” or “at rest” but can be in transiting or resting in a variety of places.
If you care about security, ask for the details.
These days it’s pretty easy to build almost any kind of software you can imagine — what’s really hard, though, is figuring out what to build. As I work on complex software systems in government, medical devices, healthcare IT, and biomedical IT I find that tackling vague requirements is one of the most pervasive and difficult problems to solve. Even the most experienced developers have a hard time building something that has not been defined well for them; a disciplined software requirements engineering approach is necessary, especially in safety critical systems. One of my colleagues in France, Abder-Rahman Ali, is currently pursuing his Medical Image Analysis Ph.D. and is passionate about applying computer science to medical imaging to come up with algorithms and systems that aid in Computer Aided Diagnosis (CAD). He’s got some brilliant ideas, especially in the use of fuzzy logic and storytelling to elicit better requirements so that CAD may become a reality some day. I asked Abder-Rahman to share with us a series of blog posts about how to tackle the problem of vague requirements. The following is his first installment, focused on storytelling and how it can be used in requirements engineering:
I remember when I was a child how my grandmother used to tell us those fictional and non-fictional stories. They still ring in my ears, even after those many years that have passed by. We used to just sit down, open our ears, stare our eyes, move around with our thoughts, and we don’t get out of such situation until the story ends. We used to make troubles sometimes, and to get us calm, we were just being called to hear that story, and the feelings above came to use again.
Phebe Cramer, in her book, Storytelling, Narrative, and the Thematic Apperception Test, mentions how storytelling has a long tradition in human history. She highlights what have been considered the significant means by which man told his story. Some of those for instance were the famous epic poems, the Iliad and the Odyssey from the ninth century B.C., the Aeneid from 20 B.C., the east Indian Mahabharata and Ramayana from the fourth century A.C., …etc. This is how history was transmitted from one generation to the other.
Storytelling Tips and Tales emphasizes that stories connect us to the past, and enlighten for us the future, lessons can be learned from stories, and information is transmitted transparently and smoothly through stories. Teachers in schools are even being encouraged to use storytelling at their classrooms. The books also believes that storytelling is an engaging process that is rewarding for both the teller and the listener. Listeners will like enter new worlds by just hearing the words of the teller. Schank and Abelson even see that psychological studies have revealed that human beings learn best from stories, in their Knowledge and Memory: The Real Story.
Having mentioned that, a requirements engineer may ask, why couldn’t we just then bring storytelling to our domain? Especially that in our work, there would be a teller and a listener. Well, could that really be?
Let us examine the relationships between story elements and a software requirement in order to answer that question.
In his book, Telling Stories: A Short Path to Writing Better Software Requirements, Ben Rinzler highlights such relationships as follows (some explanations for the points was also used from Using Storytelling to Record Requirements: Elements for an Effective Requirements Elicitation Approach):
So, yes, a relationship and an analogy exists between storytelling and software requirements.
In future posts in the series, Shahid and I will dig more deep on how storytelling could be employed in the requirements engineering process, and will also try to show how can fuzzy logic be embedded in the process to solve any issues that may be inherent in the storytelling method.
Meanwhile, drop us comments if there are specific areas of requirements engineering complex software systems that you’re especially interested in learning more about.
Our vision of providing a series of packed one day events focused on practical, relevant, and actionable health IT advice were very well received in Houston, NYC, and Santa Monica earlier this year. Our next event is in Chicago and we’re going to continue to eschew canned PowerPoint decks which limit conversations and instead deliver on the implications of major trends and operationalizable advice about where to successfully apply IT in healthcare settings. As usual, the blind promotion of tech hype is going to be replaced with and actionable insights that can be put to immediate use. Based on some of the feedback we got from the 3 earlier events this year, it looks like we struck a chord:
“IMN have brought together a one-of-a-kind venue for the HealthIMPACT forum. It offers an opportunity to explore, in-depth, the intersection of emerging models of cloud computing with solving some of our toughest problems in health information technology. It’s a great opportunity to meet national thought leaders and explore these issues at depth in an intimate setting. ” - Keith Toussaint, Executive Director, Business Development, Global Business Solutions, MAYO CLINIC
“You had a pretty engaged group yesterday. I would think you regard the meeting as successful; it was in a beautiful venue. ” - David S. Mendelson, MD, FACR, Co-Chair Integrating the Healthcare Enterprise, Professor of Radiology, Director of Radiology Information Systems Pulmonary Radiology, Senior Associate, Clinical Informatics, MOUNT SINAI MEDICAL CENTER
“[The open format] allows for valuable exchange between participants. The forum consists of important topics and fluid discussions going where the audience wants to take it.” – George Conklin, Senior Vice President and CIO, Christus Health
“HealthIMPACT seemed more focused with only high quality contributors and content. HealthIMPACT was collaborative with fewer ‘talking heads’ and more open and honest dialog. I truly felt that it was a more intimate environment for sharing.” – Zachery Jiwa, Innovation Fellow, US Department of Health and Human Services
I’m often asked why, as a health IT blogger, I wanted to lead HealthIMPACT. Here’s a three minute video overview that explains my thinking:
Based on the feedback from the Houston, NYC, and Santa Monica events and what we’ve heard from our surveys, below are some of the topics we plan to cover in Chicago on September 8th at HealthIMPACT Midwest.
All of the prepared agenda items above will be delivered in a unique and novel way so that the audience can drive the direction of the conversation. At HealthIMPACT we ask our audience to keep us honest, and they do. Some of the other topics that will be woven throughout the day include:
Data integration and system interoperability
Population Health and Patient Engagement
Clinical Decision Support
Cost & Resources
“Large collections of electronic patient records have long provided abundant, but under-explored information on the real-world use of medicines. But when used properly these records can provide longitudinal observational data which is perfect for data mining,” Duan said. “Although such records are maintained for patient administration, they could provide a broad range of clinical information for data analysis. A growing interest has been drug safety.”
In this paper, the researchers proposed two novel algorithms—a likelihood ratio model and a Bayesian network model—for adverse drug effect discovery. Although the performance of these two algorithms is comparable to the state-of-the-art algorithm, Bayesian confidence propagation neural network, by combining three works, the researchers say one can get better, more diverse results.
I saw this a few weeks ago, and while I haven't had the time to delve deep into the details of this particular advance, it did at least give me more reason for hope with respect to the big picture of which it is a part.
It brought to mind the controversy over Vioxx starting a dozen or so years ago, documented in a 2004 article in the Cleveland Clinic Journal of Medicine. Vioxx, released in 1999, was a godsend to patients suffering from rheumatoid arthritic pain, but a longitudinal study published in 2000 unexpectedly showed a higher incidence of myocardial infarctions among Vioxx users compared with the former standard-of-care drug, naproxen. Merck, the patent holder, responded that the difference was due to a "protective effect" it attributed to naproxen rather than a causative adverse effect of Vioxx.
One of the sources of empirical evidence that eventually discredited Merck's defense of Vioxx's safety was a pioneering data mining epidemiological study conducted by Graham et al. using the live electronic medical records of 1.4 million Kaiser Permanente of California patients. Their findings were presented first in a poster in 2004 and then in the Lancet in 2005. Two or three other contemporaneous epidemiological studies of smaller non-overlapping populations showed similar results. A rigorous 18-month prospective study of the efficacy of Vioxx's generic form in relieving colon polyps showed an "unanticipated" significant increase in heart attacks among study participants.
Merck's withdrawal of Vioxx was an early victory for Big Data, though it did not win the battle alone. What the controversy did do was demonstrate the power of data mining in live electronic medical records. Graham and his colleagues were able to retrospectively construct what was effectively a clinical trial based on over 2 million patient-years of data. The fact that EMR records are not as rigorously accurate as clinical trial data capture was rendered moot by the huge volume of data analyzed.
Today, the value of Big Data in epidemiology is unquestioned, and the current focus is on developing better analytics and in parallel addressing concerns about patient privacy. The HITECH Act and Obamacare are increasing the rate of electronic biomedical data capture, and improving the utility of such data by requiring the adoption of standardized data structures and controlled vocabularies.
We are witnessing the dawning of an era, and hopefully the start of the transformation of our broken healthcare system into a learning organization.
I believe if we reduce the time between intention and action, it causes a major change in what you can do, period. When you actually get it down to two seconds, it’s a different way of thinking, and that’s powerful. And so I believe, and this is what a lot of people believe in academia right now, that these on-body devices are really the next revolution in computing.
I am convinced that wearable devices, in particular heads-up devices of which Google Glass is an example, will be playing a major role in medical practice in the not-too-distant future. The above quote from Thad Starner describes the leverage point such devices will exploit: the gap that now exists between deciding to make use of a device and being able to carry out the intended action.
Right now it takes me between 15 and 30 seconds to get my iPhone out and do something useful with it. Even in its current primitive form, Google Glass can do at least some of the most common tasks for which I get out my iPhone in under five seconds, such as taking a snapshot or doing a Web search.
Closing the gap between intention and action will open up potential computing modalities that do not currently exist, entirely novel use case scenarios that are difficult even to envision before a critical mass of early adopter experience is achieved.
The Technology Review interview from which I extracted the quote raises some of the potential issues wearable tech needs to address, but the value proposition driving adoption will soon be truly compelling.
I'm adding some drill-down links below.
Practices tended to use few formal mechanisms, such as formal care teams and designated care or case managers, but there was considerable evidence of use of informal team-based care and care coordination nonetheless. It appears that many of these practices achieved the spirit, if not the letter, of the law in terms of key dimensions of PCMH.
One bit of good news about the Patient Centered Medical Home (PCMH) model: here is a study showing that in spite of considerable challenges to PCMH implementation, the transformations it embodies can be and are being implemented even in small primary care practices serving disadvantaged populations.
|ERCIM NEWS #98|
Twitter, like the Internet in general, has become a vast source of and resource for health care information. As with other tools on the Internet it also has the potential for misinformation to be distributed. In some cases this is done by accident by those with the best intentions. In other cases it is done on purpose such as when companies promote their products or services while using false accounts they created.
In order to help determine the credibility of tweets containing health-related content I suggest the using the following checklist (adapted from Rains & Karmikel, 2009):
Ultimately it is up to the individual to determine how to use health information they find on Twitter or other Internet sources. For patients anecdotal or experiential information shared by others with the same illness may be considered very credible. Others conducting research may find this a less valuable information source. Conversely a researcher may only be looking for tweets that contain reference to peer-reviewed journal articles whereas patients and their caregivers may have little or no interest in this type of resource.
Rains, S. A., & Karmike, C. D. (2009). Health information-seeking and perceptions of website credibility: Examining Web-use orientation, message characteristics, and structural features of websites. Computers in Human Behavior, 25(2), 544-553.
The altmetric movement is intended to develop new measures of production and contribution in academia. The following article provides a primer for research scholars on what metrics they should consider collecting when participating in various forms of social media.
If you participate on Twitter you should be keeping track of the number of tweets you send, how many times your tweets are replied to, re-tweeted by other users and how many @mentions (tweets that include your Twitter handle) you obtain. ThinkUp is an open source application that allows you to track these metrics as well as other social media tools such as Facebook and Google +. Please read my extensive review about this tool. This service is free.
You should register with a domain shortening service such as bit.ly, which will provide you with an API key that you can enter into applications you use to share links. This will provide a means to keep track of your click-through statistics in one location. Bit.ly records how many times a link you created was clicked on, the referrer and location of the user. Consider registering your own domain name and using it to shorten your tweets as a means of branding. In addition, you can use your custom link on electronic copies of your CV or at your own web site. This will inform you when your links have been clicked on. You should also consider using bit.ly to create links used at your web site, providing you with feedback on which are used the most often. For example, all of the links in this article were created using my custom bit.ly domain. In addition, you can tweet a link to any research study you publish to publicize as well as keep track of how many clicks are obtained. Bit.ly is a free service.
Another tool to measure your tweets is TweetReach. This service allows you to track the reach of your tweets by Twitter handle or tweet. It provides output in formats that can be saved for use elsewhere (Excel, PDF or the option to print or save your output by link). To use these latter features you must sign up for an account but the service is free.
Buffer is a tool that allows you to schedule your tweets in advance. You can also connect Buffer to your bit.ly account so links used can be included in your overall analytics. Although Buffer provides its own measures on click-through counts this can contradict what appears in bit.ly. This service is free but also has paid upgrade options available that provide more detailed analytics.
Google Scholar Citation Profile
You can set up a profile with Google Scholar based on your publication record. The metrics provided by this service include a citation count, h-index and i10-index. When someone searches your name using Google Scholar your profile will appear at the top before any of the citations. This provides a quick way to separate your articles from someone else who has the same name as you.
Google Feedburner for RSS feeds
If you maintain your own web site and use RSS feeds to announce new postings you can also collect statistics on how many times your article is clicked on. Feedburner, recently acquired by Google provides one way to measure this. You enter your RSS feed ULR and a report is generate, which can be saved in CVS format.
Journal article download statistics
Many journals provide statistics on the number of downloads of articles. Keep track of those associated with your publication by visiting the site. For example, BioMed Central (BMC) maintains an access count of the last 30 days, one year and all time for each of your publications.
Other means of contributing to the knowledge base in your field include participating on web-based forums or web sites such as Quora. Quora provides threaded discussions on topics and allows participants to both generate and respond to the question. Other users vote on your responses and points are accrued. If you want another user to answer your question you must “spend” some of your points. Providing a link to your public profile on Quora on your CV will demonstrate another form of contribution to your field.
Paper.li is a free service that curates content and renders it in a web-based format. The focus of my Paper.li is the use of technology in Canadian Healthcare. I have also created a page that appears at my web site. Metrics on the number of times your paper has been shared via Facebook, Twitter, Google + and Linked are available. This service is free.
Twylah is similar to paper.li in that it takes content and displays it in a newspaper format except it uses your Twitter feed. There is an option to create a personalized page. I use tweets.lauraogrady.ca. I also have a Twylah widget at my web site that shows my trending tweets in a condensed magazine layout. It appears in the side bar. This free service does not yet provide metrics but can help increase your tweet reach. If you create a custom link for your Twylah page you can keep track of how many people visit it.
Analytics for your web site
Log file analysis
If you maintain your own web site you can use a variety of tools to capture and analyze its use. One of the most popular applications is Google Analytics. If you are using a content management system such as WordPress there are many plug-ins that will add the code to the pages at your site and produce reports. WordPress also provides a built-in analytic available through its dashboard.
If you have access to the raw log files you could use a shareware log file program or the open source tool Piwik. These tools will provide summaries about what pages of your site are visited most frequently, what countries the visitors come from, how long visitors remain at your site and what search terms are used to reach your site.
All of this information should be included in the annual report you prepare for your department and your tenure application. This will increase awareness of altmetrics and improve our ability to have these efforts “count” as contributions in your field.